CN107085978A - A kind of control aid decision instruction generation method based on required arrival time - Google Patents
A kind of control aid decision instruction generation method based on required arrival time Download PDFInfo
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Abstract
The present invention discloses a kind of control aid decision instruction generation method based on required arrival time, and step is：Build the initial intent model of airborne vehicle, the environment model and the Mass Model needed for four-dimensional Trajectory Prediction；Trajectory Prediction is carried out to airborne vehicle, the E.T.A of initial four-dimensional flight path and way point is obtained；Using in control automated system or control aid decision-making system flight sequence, conflict Resolution function, obtain way point required arrival time；The four-dimensional flight path initial to airborne vehicle is optimized；Airborne vehicle estimated horizontal trajectory and vertical section are shown in traffic control accessory system in the air, and directly generates the control order that controller should assign to pilot.Such a method quickly generates control order by Trajectory Prediction and track optimization, and its instruction planned and flight path are simple to operate for controller and pilot, and controllability by force, and can make airborne vehicle pass through way point according to required arrival time.
Description
Technical field
The invention belongs to civil aircraft air traffic control technical field, it is related to the automation of air traffic control and intelligence
Change, air traffic control decision support tool field, more particularly to a kind of control aid decision based on required arrival time refer to
Make generation method.
Background technology
With the swift and violent growth of air traffic, spatial domain crowded state is more serious, thus caused by flight delay
Rate rise, conflict allotment difficulty increase a great problem turned into during current control works.At the same time, the operating pressure of control
Also growing day by day, the method for control by virtue of experience judged in the past has been difficult to meet the demand currently run, it is necessary in control equipment
With seek in regulatory means innovation.For air traffic control department, control aid decision-making system be it is a kind of improve efficiency,
Lighten the load and safing effective tool.
Control aid decision-making system is based on Trajectory Prediction：According to current aerospace device state, to pilot and pipe
Estimation that system person is intended to, with reference to weather information and aircraft performance, calculate state of flight of the airborne vehicle within following a period of time；
Control aid decision-making system is fast and effeciently ranked up to airborne vehicle using computer, conflicted according to the result of reckoning
Detection, and then be scheduled and conflict Resolution according to certain rule.In consideration of it, the core and key of aid decision-making system are controls
Made some time, i.e. control reaches the required arrival time (Required Time of Arrival, RTA) of a certain way point.
Following article or patent are in terms of the control aid decision-making system based on required arrival time：
The Boeing Company.Method and System of Controlling A Flight of an
Aircraft Subjected to a Required Time of Arrival Constraint:United States,
US20160379500A1[P].2016-05-24；
SHIH-YIH YOUNG M I,KRISTEN M JEROME M I.Predictable And Required Time
of Arrival Compliant Optimized Profile Descents With Four Dimensional Flight
Management System And Related Method:United States,US9193442 B1[P].2015-11-
24；
MACWILLIAMS P V,ZAKRZEWSKI E.Terminal Area Required Time of Arrival
(RTA) Concept of operations and Automation Prototype, AIAA-2008-8930 [R], 2008；
SCHARL J,HARALDSDOTTIR A,KING J,et al.A Fast-Time required time of
Arrival (RTA) model for analysis of 4D arrival management concepts, AIAA-2008-
7027[R],2008.
It is important to note, however, that the studies above still rests on operation conceptual design and prototype system Qualify Phase at present,
There are following two defects from practical application：One is that control accessory system is only to provide " the effect that should be reached for controller
Really ", not specific method of control, this performance difficulty for controller, being still difficult to solution makes airborne vehicle is punctual to cross point
The problem of；Two be to be completed based on the trajectory planning of required arrival time by airborne, compared to the detection of ground airbome weather
The airborne vehicle that scope is small, can not consider in spatial domain, while the strategy awaits air-ground making a breakthrough property of data communication technology
Progress.
The content of the invention
The purpose of the present invention, is to provide a kind of control aid decision instruction generation method based on required arrival time,
It quickly generates control order by Trajectory Prediction and track optimization, and its instruction planned is with flight path to controller and pilot
Speech is simple to operate, and controllability is strong, and airborne vehicle can be made to pass through way point according to required arrival time.
In order to reach above-mentioned purpose, solution of the invention is：
A kind of control aid decision instruction generation method based on required arrival time, comprises the following steps：
Step 1, the initial intent model of airborne vehicle, the environment model and the particle mould needed for four-dimensional Trajectory Prediction are built
Type；
Step 2, according to the intent model set up in step 1, environmental model, Mass Model, flight path is carried out to airborne vehicle pre-
Survey, obtain the E.T.A of initial four-dimensional flight path and way point；
Step 3, using in control automated system or control aid decision-making system flight sequence, conflict Resolution function,
Obtain the required arrival time of way point；
Step 4, the required arrival time in step 3, the four-dimensional flight path initial to airborne vehicle is optimized；
Step 5, airborne vehicle estimated horizontal trajectory and vertical section are shown in traffic control accessory system in the air, and directly
Deliver a child into the control order that controller should assign to pilot.
In above-mentioned steps 1, the construction method of the initial intent model of airborne vehicle is：Sat according to flight plan and way point
Mark, sets up the cross track of airborne vehicle；With reference to database coding schedule and control turnover agreement, the boat to be passed through of airborne vehicle is determined
The rate limitation and height limitation of waypoint；Thus the initial intent model of airborne vehicle is obtained.
In above-mentioned steps 1, the construction method of the environment model is：
Step 1a, according to temperature deviation and pressure altitude, determines atmospheric temperature T：
T=T0+ΔT+βT·Hp
Wherein, T0=288.15K, represents the temperature at mean sea level under international Standard atmosphere conditions；Δ T represents temperature
Spend deviation；HpRepresent pressure altitude；βT=-0.0065K/m, represents Lapse rate of air temperature；
Step 1b, according to atmospheric temperature T, determines atmospheric pressure p：
Wherein, p0=101325Pa, represents the air pressure under international Standard atmosphere conditions；g0=9.80665m/s2, table
Show acceleration of gravity；R=287.05287m2/(K·s2), represent air constant；
Step 1c, according to temperature T and pressure p, determines atmospheric density ρ：
Step 1d, the wind direction and wind velocity in weather forecast, with reference to atmospheric temperature, atmospheric pressure and atmospheric density, is set up
The environmental model of airborne vehicle operation.
In above-mentioned steps 1, the construction method of Mass Model is：
Step 10a, calculates the thrust of aircraft engine, its takeoff thrust capability Thrmax climbSuch as following formula：
Thrmax climb=CTc,1·(1-h/CTc,2+CTc,3·h2)·(1-CTc,5·ΔT)
Wherein, h is geodetic height, CTc,1、CTc,2、CTc,3And CTc,5It is thrust coefficient；
Step 10b, airborne vehicle resistance is calculated according to following formula：
Wherein, VTASFor airborne vehicle true air speed；CDFor resistance coefficient, S is wing area of reference；
Step 10c, airborne vehicle kinematical equation is as follows：
Wherein, m represents airborne vehicle quality, and d/dt represents time diffusion；
The equation is derived as：
Wherein, defineF { M } is energy distribution coefficient；
Step 10d, airborne vehicle Mass Model is set up by airborne vehicle thrust, resistance and kinematical equation.
In above-mentioned steps 3, control automated system or control the aid decision-making system arrival time needed for airborne vehicle is specified
When, need to be in time window；If required arrival time exceeds time window scope, entered by the intent model in set-up procedure 1
Row adjustment.
Above-mentioned steps 4 are comprised the following steps that：
Step 41, the initial four-dimensional flight path generated by step 2, according to an obligatory point in intent model to it is next about
Spot, is split as multiple legs；
Step 42, each leg is split as two sub- legs again：Completion slows down or accelerates determining for the process of climbing
Justice is sub- leg 1, and it is sub- leg 2 to complete the flat definition for flying to next obligatory point of constant speed；
Step 43, during the track optimization based on required arrival time, sub- leg 2 is split as two constant speed again
Put down winged sub- leg：Winged sub- leg 2a is put down positioned at constant speed before sub- leg 1, positioned at the flat son boat flown of constant speed after sub- leg 1
Section 2b；
Step 44, being located at the leg split out in step 41 needs the time adjusted to be Δ t, sets up below equation：
t0=t3
Δ t=t2-t6
t1-t0=t5-t4
Wherein, t0Represent the sub- time started of leg 1, t before optimization1Represent the sub- end time of leg 1 or sub- leg 2 before optimization
Time started, t2Represent the sub- end time of leg 2 before optimization；t3Represent sub- leg 2a time starteds, t after optimization4Represent after optimization
Sub- leg 2a end times or the time started of sub- leg 1, t5When representing that the sub- end time of leg 1 or sub- leg 2b start after optimization
Between, t6Represent the sub- leg 2b end times after optimization；
Step 45, the distance loss during turning, the level that airborne vehicle is flown in each leg before and after optimization are not considered
Apart from equal：
Wherein, f1Represent the Velocity-time function before optimization, f2Represent the Velocity-time function after optimization；
Step 46, time Δ t can adjust to each leg and makes following limitation：
Decline leg：
Climb leg：
Wherein, VTAS0Represent the true air speed (True Airspeed, TAS) of the sub- starting point of leg 1, VTAS1Represent sub- leg 1
The true air speed of end point；
Step 47, the difference that the airborne vehicle after optimization spends a time and required arrival time is compared, if in error range
Optimization is completed；If beyond error range, adjusting and optimizing amount simultaneously optimizes, spends a time until airborne vehicle and arrived with required again
Difference up to the time is in error range.
After such scheme, the present invention proposes a kind of new flight path generation and optimal way, and the control on ground is auxiliary
The trajectory planning based on required arrival time, and the control order that should be directly assigned to controller's offer are completed in auxiliary system,
So as to aid in controller's decision-making, reach and improve control context-aware, reduce the purpose of control workload.Specifically, this hair
It is bright to have the advantages that：
(1) the track optimization mode that uses of the present invention is that the fractionation of track will not with combining, therefore during optimization
Change the original decline deceleration of airborne vehicle and acceleration is climbed mode, the performance of airborne vehicle is unaffected；Come for pilot
Say, the flight path after optimization does not change original mode of operation, only relate to the opportunity of operation；And for controller, clearly
Control order point and regulation model, can very easily assign control order, while improving control accuracy, mitigate negative
Lotus；
(2) practicality of the present invention is strong, real-time track optimizing and amendment is supported, even if because human error causes suitably may be used
The deviation of control, route optimization method of the invention can be modified in the later stage, eliminate preamble deviation；
(3) present invention can make airborne vehicle reach specified way point in required arrival time；
(4) present invention provides direct control to controller and advised, is favorably improved control context-aware, reduction control work
Make load.
Brief description of the drawings
Fig. 1 is the flow chart of the present invention；
Fig. 2 is the initial intent model generation schematic diagram of airborne vehicle；
Fig. 3 is environmental model generation schematic diagram；
Fig. 4 is Mass Model generation schematic diagram；
Fig. 5 is track optimization process schematic；
Fig. 6 is to decline the Velocity-time diagrammatic cross-section in the track optimization of leg；
Fig. 7 is control order generation and display schematic diagram in control aid decision-making system.
Embodiment
Below with reference to accompanying drawing, technical scheme and beneficial effect are described in detail.
As shown in figure 1, the present invention provides a kind of control aid decision instruction generation method based on required arrival time, bag
Include following steps：
Step 11, according to flight plan and air route point coordinates, the cross track of airborne vehicle is set up, with reference to database coding schedule
With control turnover agreement, the rate limitation and height limitation of the airborne vehicle way point to be passed through are determined, airborne vehicle is thus obtained
Initial intent model；According to meteorological measuring and weather forecast, the environmental model during airborne vehicle operation is set up, including not
With height and the data such as the atmospheric temperature of diverse location, atmospheric pressure, atmospheric density and wind field；According to airborne vehicle kinetic model
With kinematical equation, airborne vehicle equation of particle motion is set up, based on the performance ginseng in airborne vehicle basic performance database (BADA)
Number, sets up the Mass Model of airborne vehicle；
Step 12, with reference to the intent model in step 11, environmental model, Mass Model, Trajectory Prediction is carried out to airborne vehicle,
And obtain the E.T.A (Estimated Time of Arrival, ETA) of way point；Initial four-dimensional flight path passes through
The cumulative recursion of step-ahead prediction is formed, and next constraint in the current state and intent model of airborne vehicle is first compared before step-ahead prediction
Speed/height relationships of point, the flying method that should be used is as shown in table 1：
Table 1
In table 1, VCAS1Represent the calibrated airspeed (Calibrated Air Speed, CAS) of airborne vehicle current point, VCAS2Table
Illustrate the calibrated airspeed of next obligatory point in graph model；h1Represent the height (Altitude, ALT) of airborne vehicle current point, h2Table
Illustrate the height of next obligatory point in graph model.
Step 13, using in control automated system or control aid decision-making system flight sequence, conflict Resolution function,
Obtain the required arrival time (Required Time of Arrival, RTA) of way point；A level is navigated in step 12
Road carries out that during Trajectory Prediction the E.T.A of way point can be obtained, while when obtaining the earliest of way point and reaching the latest
Between, this time interval of arrival time is referred to as time window earliest and the latest；Control automated system or control aid decision system
System, should be in time window in specified airborne vehicle RTA；If because the reason RTA such as conflict exceed time window scope, should pass through
Change horizontal route or waiting strategy to be adjusted, i.e. intent model in set-up procedure 11；
Step 14, based on the required arrival time in step 13, according to the four-dimension based on required arrival time in the present invention
Route optimization method, is optimized to initial four-dimensional flight path；
Step 15, airborne vehicle estimated horizontal trajectory and vertical section are shown in traffic control accessory system in the air, and
Directly generate the control order that controller should assign to pilot.
Fig. 2 is the initial four-dimensional flight path generation schematic diagram of airborne vehicle, specifically includes following steps：
Step 21, according to flight plan and air route point coordinates, the cross track of airborne vehicle is set up；
Step 22, with reference to database coding schedule and control turnover agreement, the speed of the airborne vehicle way point to be passed through is determined
Degree limitation and height limitation；
Step 23, joint step 21, step 22 set up the initial intent model of airborne vehicle.
Fig. 3 is that environmental model generates schematic diagram, specifically includes following steps：
Step 31, according to temperature deviation and pressure altitude, atmospheric temperature T is determined：
T=T0+ΔT+βT·Hp
In above formula, T0=288.15K, represents the temperature at mean sea level under international Standard atmosphere conditions；Δ T is represented
Temperature deviation；HpRepresent pressure altitude；βT=-0.0065K/m, represents Lapse rate of air temperature；
Step 32, according to atmospheric temperature T, atmospheric pressure p is determined：
In above formula, p0=101325Pa, represents the air pressure under international Standard atmosphere conditions；g0=9.80665m/s2,
Represent acceleration of gravity；R=287.05287m2/(K·s2), represent air constant；
Step 33, according to temperature T and pressure p, atmospheric density ρ is determined：
Step 34, the wind direction and wind velocity in weather forecast, with reference to atmospheric temperature, atmospheric pressure and atmospheric density, sets up
The environmental model of airborne vehicle operation；
Fig. 4 is that Mass Model generates schematic diagram, is comprised the following steps that：
Step 41, the thrust of aircraft engine, its takeoff thrust capability Thr are calculatedmax climbSuch as following formula：
Thrmax climb=CTc,1·(1-h/CTc,2+CTc,3·h2)·(1-CTc,5·ΔT)
In above formula, h is geodetic height, CTc,1、CTc,2、CTc,3And CTc,5It is thrust coefficient, referring to airborne vehicle basic data
(BADA), and take off/climbing/cruise/decline/enter the function that near/thrust for landing may be regarded as Maximum Climb Thrust, it is and residing
Height and mission phase are related；
Step 42, airborne vehicle resistance is calculated：
In above formula, VTASFor airborne vehicle true air speed；CDFor resistance coefficient, S is wing area of reference, and each coefficient is referring to aviation
Device basic data (BADA)；And the resistance coefficient that aircraft takeoff/climbing/is cruised/entered under closely/landing configuration is CDCorrelation
Function；
Step 43, airborne vehicle kinematical equation：
In above formula, m represents airborne vehicle quality, and d/dt represents time diffusion；
Further, the equation can be derived as：
In above formula, definitionF { M } is energy distribution coefficient；Values of the f { M } in each stage
And calculate referring to airborne vehicle basic data (BADA)；
Step 44, airborne vehicle Mass Model is set up by airborne vehicle thrust, resistance and kinematical equation；
Fig. 5 is track optimization process schematic, is comprised the following steps that：
Step 51, multiple legs are split as to next obligatory point according to an obligatory point in intent model；Declining
In leg, may using slowing down, constant speed decline, slow down it is flat fly, constant speed is flat flies four kinds of flying methods；In leg of climbing
In, it may be climbed using acceleration, constant speed is climbed, accelerate flat winged, constant speed is flat to fly four kinds of flying methods；But in two kinds of boat
Duan Zhong, constant speed puts down winged flying method and often follows other three kinds of flying methods closely；Therefore each leg can be split as two again
Individual sub- leg：The definition for completing to slow down process is sub- leg 1, and it is son to complete the flat definition for flying to next obligatory point of constant speed
Leg 2；
Step 52, it is necessary to which sub- leg 2 is split as into two again during the track optimization based on required arrival time
Constant speed puts down winged sub- leg：Winged sub- leg 2a is put down positioned at constant speed before sub- leg 1, puts down what is flown positioned at constant speed after sub- leg 1
Sub- leg 2b；
Step 53, by three sub- legs after fractionation：Sub- leg 1, sub- leg 2a, sub- leg 2b is carried out according to following rule
Restructuring：
(a) being located at the leg split out in step 51 needs the time adjusted to be Δ t, sets up below equation：
t0=t3
Δ t=t2-t6
t1-t0=t5-t4
In above formula, t0Represent the sub- time started of leg 1, t before optimization1Represent the sub- end time of leg 1 or sub- leg before optimization
2 time starteds, t2Represent the sub- end time of leg 2 before optimization；t3Represent sub- leg 2a time starteds, t after optimization4Represent optimization
Sub- leg 2a end times or the time started of sub- leg 1, t afterwards5Represent that the sub- end time of leg 1 or sub- leg 2b start after optimization
Time, t6Represent the sub- leg 2b end times after optimization；
(b) the distance loss during turning, the horizontal range that airborne vehicle is flown in each leg before and after optimization are not considered
It is equal：
In above formula, f1Represent the Velocity-time function before optimization, f2Represent the Velocity-time function after optimization；
(c) time Δ t can adjust to each leg and makes following limitation：
Decline leg：
Climb leg：
In above formula, VTAS0Represent the true air speed (True Airspeed, TAS) of the sub- starting point of leg 1, VTAS1Represent sub- leg
The true air speed of 1 end point.
The speed that airborne vehicle passes through turning point is changed when step 54, due to optimization, causes the change of radius of turn, and then
Cause the change of whole horizontal range.In order to eliminate the time error produced by total distance change, compare the airborne vehicle after optimization
Some time and RTA difference are spent, optimizes if in error range and completes；If beyond error range, adjusting and optimizing amount and again
Optimize, until airborne vehicle crosses a time and RTA difference in error range.
Fig. 6 is declines the Velocity-time diagrammatic cross-section in the track optimization of leg, by the fractionation to leg with combining,
The time of airborne vehicle from way point to a next way point shortens Δ t, and will not change initial four-dimensional flight path in way point
Height/speed；Airborne vehicle flies according to section, and when reaching height/velocity variations point in section, controller is under pilot
Up to once command.
Fig. 7 is control order generation and display schematic diagram in control accessory system.(a) is partly command prompt area in Fig. 7,
Black vertical line represents that instruction performs line below time shaft；The respective progress bar of every frame airborne vehicle correspondence, progress bar can be over time
Axle is moved to the left together：Progress bar is divided into two states, and the expression of black performs section (velocity variations or height change), in vain
The flat winged section of the expression constant speed of color；The right " instruction area " represents control order；When the execution section of black performs line close to instruction, pipe
System person can assign control order to pilot.(b) is partly that airborne vehicle level after track optimization is marched into the arena track and height in Fig. 7
Degree, velocity profile schematic diagram.
The technological thought of above example only to illustrate the invention, it is impossible to which protection scope of the present invention is limited with this, it is every
According to technological thought proposed by the present invention, any change done on the basis of technical scheme each falls within the scope of the present invention
Within.
Claims (6)
1. a kind of control aid decision instruction generation method based on required arrival time, it is characterised in that comprise the following steps：
Step 1, the initial intent model of airborne vehicle, the environment model and the Mass Model needed for four-dimensional Trajectory Prediction are built；
Step 2, according to the intent model set up in step 1, environmental model, Mass Model, Trajectory Prediction is carried out to airborne vehicle, obtained
To the E.T.A of initial four-dimensional flight path and way point；
Step 3, using in control automated system or control aid decision-making system flight sequence, conflict Resolution function, obtain
The required arrival time of way point；
Step 4, the required arrival time in step 3, the four-dimensional flight path initial to airborne vehicle is optimized；
Step 5, airborne vehicle estimated horizontal trajectory and vertical section are shown in traffic control accessory system in the air, and is directly given birth to
The control order that should be assigned into controller to pilot.
2. a kind of control aid decision instruction generation method based on required arrival time as claimed in claim 1, its feature
It is：In the step 1, the construction method of the initial intent model of airborne vehicle is：According to flight plan and air route point coordinates, build
The cross track of vertical airborne vehicle；With reference to database coding schedule and control turnover agreement, the airborne vehicle way point to be passed through is determined
Rate limitation and height limitation；Thus the initial intent model of airborne vehicle is obtained.
3. a kind of control aid decision instruction generation method based on required arrival time as claimed in claim 1, its feature
It is：In the step 1, the construction method of the environment model is：
Step 1a, according to temperature deviation and pressure altitude, determines atmospheric temperature T：
T=T0+ΔT+βT·Hp
Wherein, T0=288.15K, represents the temperature at mean sea level under international Standard atmosphere conditions；Δ T represents that temperature is inclined
Difference；HpRepresent pressure altitude；βT=-0.0065K/m, represents Lapse rate of air temperature；
Step 1b, according to atmospheric temperature T, determines atmospheric pressure p：
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Wherein, p0=101325Pa, represents the air pressure under international Standard atmosphere conditions；g0=9.80665m/s2, represent weight
Power acceleration；R=287.05287m2/(K·s2), represent air constant；
Step 1c, according to temperature T and pressure p, determines atmospheric density ρ：
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Step 1d, the wind direction and wind velocity in weather forecast, with reference to atmospheric temperature, atmospheric pressure and atmospheric density, sets up aviation
The environmental model of device operation.
4. a kind of control aid decision instruction generation method based on required arrival time as claimed in claim 1, its feature
It is：In the step 1, the construction method of Mass Model is：
Step 10a, calculates the thrust of aircraft engine, its takeoff thrust capability Thrmax climbSuch as following formula：
Thrmax climb=CTc,1·(1-h/CTc,2+CTc,3·h2)·(1-CTc,5·ΔT)
Wherein, h is geodetic height, CTc,1、CTc,2、CTc,3And CTc,5It is thrust coefficient；
Step 10b, airborne vehicle resistance is calculated according to following formula：
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Wherein, VTASFor airborne vehicle true air speed；CDFor resistance coefficient, S is wing area of reference；
Step 10c, airborne vehicle kinematical equation is as follows：
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<mi>d</mi>
<mi>h</mi>
</mrow>
<mrow>
<mi>d</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>+</mo>
<msub>
<mi>mV</mi>
<mrow>
<mi>T</mi>
<mi>A</mi>
<mi>S</mi>
</mrow>
</msub>
<mfrac>
<mrow>
<msub>
<mi>dV</mi>
<mrow>
<mi>T</mi>
<mi>A</mi>
<mi>S</mi>
</mrow>
</msub>
</mrow>
<mrow>
<mi>d</mi>
<mi>t</mi>
</mrow>
</mfrac>
</mrow>
Wherein, m represents airborne vehicle quality, and d/dt represents time diffusion；
The equation is derived as：
<mrow>
<mfrac>
<mrow>
<mi>d</mi>
<mi>h</mi>
</mrow>
<mrow>
<mi>d</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>=</mo>
<mfrac>
<mrow>
<mo>(</mo>
<mi>T</mi>
<mi>h</mi>
<mi>r</mi>
<mo>-</mo>
<mi>D</mi>
<mo>)</mo>
<mo>&CenterDot;</mo>
<msub>
<mi>V</mi>
<mrow>
<mi>T</mi>
<mi>A</mi>
<mi>S</mi>
</mrow>
</msub>
</mrow>
<mrow>
<msub>
<mi>mg</mi>
<mn>0</mn>
</msub>
</mrow>
</mfrac>
<msup>
<mrow>
<mo>&lsqb;</mo>
<mn>1</mn>
<mo>+</mo>
<mrow>
<mo>(</mo>
<mfrac>
<msub>
<mi>V</mi>
<mrow>
<mi>T</mi>
<mi>A</mi>
<mi>S</mi>
</mrow>
</msub>
<msub>
<mi>g</mi>
<mn>0</mn>
</msub>
</mfrac>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<mfrac>
<mrow>
<msub>
<mi>dV</mi>
<mrow>
<mi>T</mi>
<mi>A</mi>
<mi>S</mi>
</mrow>
</msub>
</mrow>
<mrow>
<mi>d</mi>
<mi>h</mi>
</mrow>
</mfrac>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
</mrow>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>=</mo>
<mo>&lsqb;</mo>
<mfrac>
<mrow>
<mo>(</mo>
<mi>T</mi>
<mi>h</mi>
<mi>r</mi>
<mo>-</mo>
<mi>D</mi>
<mo>)</mo>
<mo>&CenterDot;</mo>
<msub>
<mi>V</mi>
<mrow>
<mi>T</mi>
<mi>A</mi>
<mi>S</mi>
</mrow>
</msub>
</mrow>
<mrow>
<msub>
<mi>mg</mi>
<mn>0</mn>
</msub>
</mrow>
</mfrac>
<mo>&rsqb;</mo>
<mi>f</mi>
<mo>{</mo>
<mi>M</mi>
<mo>}</mo>
</mrow>
Wherein, defineF { M } is energy distribution coefficient；
Step 10d, airborne vehicle Mass Model is set up by airborne vehicle thrust, resistance and kinematical equation.
5. a kind of control aid decision instruction generation method based on required arrival time as claimed in claim 1, its feature
It is：In the step 3, control automated system or control aid decision-making system in arrival time needed for specifying airborne vehicle,
Need to be in time window；If required arrival time exceeds time window scope, adjusted by the intent model in set-up procedure 1
It is whole.
6. a kind of control aid decision instruction generation method based on required arrival time as claimed in claim 1, its feature
It is：The step 4 is comprised the following steps that：
Step 41, the initial four-dimensional flight path generated by step 2, according to an obligatory point in intent model to next constraint
Point, is split as multiple legs；
Step 42, each leg is split as two sub- legs again：Complete to slow down or accelerate the definition of the process of climbing be
Sub- leg 1, it is sub- leg 2 to complete the flat definition for flying to next obligatory point of constant speed；
Step 43, during the track optimization based on required arrival time, sub- leg 2 is split as two constant speed again flat winged
Sub- leg：Winged sub- leg 2a is put down positioned at constant speed before sub- leg 1, winged sub- leg 2b is put down positioned at constant speed after sub- leg 1；
Step 44, being located at the leg split out in step 41 needs the time adjusted to be Δ t, sets up below equation：
t0=t3
Δ t=t2-t6
t1-t0=t5-t4
Wherein, t0Represent the sub- time started of leg 1, t before optimization1Represent that the sub- end time of leg 1 or sub- leg 2 start before optimization
Time, t2Represent the sub- end time of leg 2 before optimization；t3Represent sub- leg 2a time starteds, t after optimization4Represent son boat after optimization
Section 2a end times or the time started of sub- leg 1, t5Represent the sub- end time of leg 1 or sub- leg 2b time starteds, t after optimization6
Represent the sub- leg 2b end times after optimization；
Step 45, the distance loss during turning, the horizontal range that airborne vehicle is flown in each leg before and after optimization are not considered
It is equal：
<mrow>
<msubsup>
<mo>&Integral;</mo>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
</msubsup>
<msub>
<mi>f</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>t</mi>
<mo>=</mo>
<msubsup>
<mo>&Integral;</mo>
<msub>
<mi>t</mi>
<mn>4</mn>
</msub>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
</msubsup>
<msub>
<mi>f</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>t</mi>
</mrow>
<mrow>
<msubsup>
<mo>&Integral;</mo>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
</msubsup>
<msub>
<mi>f</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>t</mi>
<mo>=</mo>
<msubsup>
<mo>&Integral;</mo>
<msub>
<mi>t</mi>
<mn>3</mn>
</msub>
<msub>
<mi>t</mi>
<mn>6</mn>
</msub>
</msubsup>
<msub>
<mi>f</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>t</mi>
</mrow>
Wherein, f1Represent the Velocity-time function before optimization, f2Represent the Velocity-time function after optimization；
Step 46, time Δ t can adjust to each leg and makes following limitation：
Decline leg：
Climb leg：
Wherein, VTAS0Represent the true air speed (True Airspeed, TAS) of the sub- starting point of leg 1, VTAS1Represent that sub- leg 1 is terminated
The true air speed of point；
Step 47, compare the difference that the airborne vehicle after optimization spends a time and required arrival time, optimize if in error range
Complete；If beyond error range, adjusting and optimizing amount is simultaneously optimized again, when airborne vehicle spends a time with required arrival
Between difference in error range.
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